Guest Editorial Special Section on Tiny Machine Learning in Internet of Unmanned Aerial Vehicles

With the rapid development of ubiquitous networks and smart devices, artificial intelligence-based unmanned aerial vehicles (UAVs) are drawing more and more attention. The rise in popularity of deep neural networks (DNNs) has spawned a research effort to deploy various kinds of DNN models on vehicles. They have been used to accomplish complicated vehicular tasks and enable the construction of intelligent vehicular networks. Despite the promising prospects, how to train and run them on resource-limited and hardware-constrained UAVs faces huge challenges. Furthermore, the tradeoff between accuracy and latency needs to be considered while reducing the computational cost of DNN training.